63 results about "Patient input" patented technology

A system for administering treatment with a medical device includes a medical device capable of delivering a medical treatment to a patient. An electronic computing device has a processor, computer-readable memory, and a power supply. The electronic computing device is in communication with the medical device. A patient interface is in communication with the electronic computing device and the medical device. The electronic computing device is configured to: receive an initial electronic treatment protocol; communicate the initial electronic treatment protocol to the medical device to enable an initial treatment of the patient; receive patient input through the patient interface; receive an updated treatment protocol based on the patient input; and communicate the updated treatment protocol to the medical device to enable an updated treatment of the patient.

A system for administering transcranial neuromodulation (TNM) treatment with a medical device capable of delivering a TNM treatment to a patient including an electronic computing device has a processor, computer-readable memory, and a power supply, in communication with the TNM device. A patient interface is in communication with the electronic computing device and the TNM device. The electronic computing device is configured to: receive an initial TNM treatment protocol; communicate same to the TNM device to enable initial TNM treatment; receive patient input through the patient interface; receive an updated TNM treatment protocol based on patient input; and communicate updated TNM treatment protocol to the TNM device to enable updated TNM treatment of the patient.

The invention relates to a patient examination item recommendation method based on a medical knowledge graph. The method comprises the steps that firstly, historical data in the medical field is acquired, key information is extracted from the historical data to generate an entity relation triple, and then a medical knowledge graph is constructed; then, generating a patient state sub-graph based on patient input information, processing the medical knowledge graph by adopting an improved TransD model, and determining unique representation of an entity-relationship pair; mapping the patient state sub-map to a unique representation space, obtaining vector representation of a patient and an examination item related entity, and calculating a similarity value between vectors to obtain a similarity value matrix; and finally, performing priority ranking on the inspection items according to the matrix, and generating a final recommendation list through threshold screening and combination with graph neural network verification, optimization and adjustment of priorities. By adopting the method, examination items can be accurately recommended for patients, doctors are assisted to improve the treatment efficiency, the queuing time of the patients is shortened, and the medical experience of the patients is remarkably improved.

The invention relates to the field of medical information processing, and discloses a reinforcement learning and cooperation system based on Internet hospital medical dialogues and medical records, and the system comprises a complete dialogue chain obtaining module which is used for obtaining a complete dialogue chain of patient input-large model reply-doctor modification in each round; the feedback format construction module is used for constructing a structured feedback format based on the complete dialogue chain to serve as a training sample of reinforcement learning, and the structured feedback format comprises input content, original reply, doctor editing content, editing behavior labels and semantic difference; and the reinforcement learning optimization module is used for introducing a reinforcement learning algorithm PPO on the basis of the existing supervised fine tuning model, and executing reinforcement learning optimization oriented to the medical dialogue system based on the training sample. According to the method, the problems that in an existing medical inquiry dialogue system, the response lacks reasoning transparency, the model cannot be continuously optimized, doctor feedback is not utilized, and the system request pressure is uncontrollable can be solved.

To provide an examinee candidate extraction system for promptly and efficiently extracting an examinee candidate of a clinical research by utilizing information collected on the basis of the will of a patient, an examinee candidate extraction device, an examinee candidate extraction method and a program.SOLUTION: An examinee candidate extraction system 1 includes an integrated repository 11 and an examinee candidate extraction device 17. The integrated repository 11 stores in an associated manner, medical information of a patient which is inputted or generated by a medical institution and previously permitted by the patient, the physical information of the patient inputted or generated by the patient and previously permitted by the patient, and information relating to the will of the patient to be an examinee candidate. The examinee candidate extraction device 17 extracts from the integrated repository 11 the patient having the predetermined medical information and the physical information from among the patients having the wills to be the examinee candidate in accordance with a selection condition or algorithm.SELECTED DRAWING: Figure 1

The present disclosure generally relates to a computer system (100) and a computerized method (300) for predicting a kidney condition for a patient using a machine learning model (200). The method (300) comprises: obtaining (310,330) a current patient input dataset and a historical eGFR input dataset associated with the patient; generating (320) a patient input vector representation (222) using the current patient input dataset and an input linear layer (220); generating (340) an eGFR vector representation (242) using the historical eGFR input dataset and a first input machine learning module (240); concatenating (350) the patient input and eGFR vector representations (222,242) into an output vector representation (260); and generating (360) a prediction output (280) using the output vector representation (260) and an output machine learning module (270), the prediction output (280) comprising a risk assessment of the patient contracting the kidney condition.

System (100) for personalized condition-based matching of health networks using artificial intelligence and population health data, comprising: (a) a patient profiling module configured to collect and analyse individual health data from electronic health records, wearable devices and patient inputs to identify current medical conditions and generate dynamic health profiles; (b) a population health intelligence engine configured to aggregate and analyze population-level health data to identify regional disease trends, treatment outcomes, and provider performance; c) an AI-based network matching algorithm configured to compare individual health conditions with provider capabilities, historical outcomes, availability, and other contextual parameters to generate rated recommendations for healthcare providers; (d) a provider profiling and network indexing module configured to store, index and update provider and network information, including specialization, certifications, outcomes, availability and treatment capacities; (e) a decision support interface configured to present patients or clinicians with personalized, explainable recommendations for healthcare providers based on clinical relevance, patient preferences and system intelligence; (f) a feedback and learning optimization module configured to continuously collect patient outcomes, satisfaction, and treatment effectiveness to refine and retrain AI models; and g) a data security and compliance layer configured to ensure the secure handling of patient data, enforce access control, and ensure compliance with data protection standards such as HIPAA and GDPR.

The invention discloses a traditional Chinese medicine syndrome and prescription matching recommendation method based on a graph neural network. The method comprises the following steps: S1, establishing a traditional Chinese medicine knowledge graph containing a node and edge relationship; s2, performing data preprocessing on the traditional Chinese medicine knowledge graph; s3, generating feature vectors of syndrome nodes and feature vectors of prescription nodes; s4, mapping the syndrome information of the patient to the generated feature vector space; s5, generating a prescription matching candidate set; s6, finally determining an optimal prescription combination; and S7, based on the optimized optimal prescription combination, outputting a prescription recommendation result containing prescription composition, medicinal material dosage and indication description, and carrying out interpretability analysis on the recommendation result. According to the method, the high-precision matching of the patient input features and the prescription features is realized, the potential semantic relationship in the traditional Chinese medicine knowledge graph can be more accurately captured, and the matching precision is remarkably improved.

The invention discloses a traditional Chinese medicine intelligent diagnosis and treatment platform construction method based on combination of a large model and two-channel retrieval, the diagnosis and treatment platform is used for inputting and outputting traditional Chinese medicine diagnosis and treatment suggestions according to a patient based on a traditional Chinese medicine knowledge graph, and the method comprises the following steps: step S1, collecting clinical medical record data and preprocessing the data; s2, constructing a traditional Chinese medicine knowledge graph based on a large language model; s3, constructing a traditional Chinese medicine prescription model based on a two-channel retrieval mechanism by fusing the large language model and the traditional Chinese medicine knowledge graph; s4, performing fusion processing on the dual-channel information retrieval result, and outputting a prescription after comprehensive reasoning; and S5, matching the model generation prescription with a clinical famous doctor prescription, and verifying the accuracy of the traditional Chinese medicine prescription model. The famous doctor intelligent inheriting cloud platform is constructed, the effects of remarkably improving inheriting efficiency and breaking through traditional Chinese medicine diagnosis and treatment standardization are achieved, and a good foundation is laid for subsequent famous doctor intelligent inheriting product landing popularization.

The application relates to the technical field of human resource management, in particular to a medical staff scheduling system based on medical staff skills, which comprises a standard skill input and classification device, which is used for inputting the working skills of each department, dividing the same working skills of each department into general skills, and dividing the special working skills of each department into special skills; a department patient input device, which obtains the treatment information of patients in each department ward, extracts the predicted workload of each patient in the next scheduling cycle, and counts the predicted workload of each department; the predicted workload comprises the execution times of each general skill and the execution times of each special skill; the system realizes cross-department dynamic scheduling by constructing a hospital-level skill resource pool and a demand prediction mechanism, standardizes the general skills into shared resources, and enables medical staff to flexibly support departments with high demand peaks.

The invention relates to a computer-implemented method for determining spatially resolved radiation load information of a patient when conducting an examination with an imaging X-ray apparatus having an X-ray radiator for outputting an X-ray field for conducting the examination, wherein patient input dose information is determined for determining the radiation load information, wherein the pre-dose information is determined in the case of use of a matching filter arranged between the patient and the X-ray radiator, which causes a non-uniform dose distribution in a plane perpendicular to a central ray of the X-ray field, the pre-dose information describing a uniform distribution of the X-ray dose acting on the patient without the matching filter; dose distribution information is calculated using the pre-dose information by means of a filter model, which describes at least the dose distribution of the X-ray dose acting on the patient in the part of the X-ray field covered by the matching filter; and the patient input dose information is determined using the dose distribution information.

The utility model discloses a hepatobiliary double-headed infusion apparatus, which relates to the technical field of medical infusion apparatuses, and comprises a first liquid inlet tube, a second liquid inlet tube, a conduit, two temporary storage buckets, a first liquid inlet tube, a second liquid inlet tube, a second liquid inlet tube, a second liquid inlet tube, a second liquid inlet tube, a third liquid inlet tube and a fourth liquid inlet tube, the two temporary storage hoppers are respectively communicated with the first liquid inlet pipe and the second liquid inlet pipe; the detection assembly is mounted on the outer surfaces of the dripping bucket and the temporary storage bucket, and the detection mechanism is used for detecting liquid level changes in the dripping bucket and the temporary storage bucket; and the control mechanism is arranged above the temporary storage hopper, and the control mechanism comprises a control assembly and a stopping assembly. Through the arrangement of the detection assembly and the control mechanism, after one bottle of liquid medicine is completely infused, another bottle of liquid medicine can be automatically infused for a patient, and therefore the problem that the infusion bottle cannot be replaced in time when the patient lacks action force and is unattended is solved.

The following relates generally to improved clinical symptom analysis. In some embodiments, one or more processors: (1) receive patient input data; (2) obtain patient survey data representing the patient's condition; (3) determine a trend in the patient survey data using a determination algorithm; (4) apply the generative AI algorithm to the patient input data, the patient survey data, and the trend in the patient survey data to produce a report of the trend of the patient's condition; and / or (5) display the report on a display device.

Methods and systems for providing context for alarms and resolving alarms using a virtual agent are described. Inputs including imaging, patient information, and aural, visual, and mechanical patient inputs are analyzed to provide context for an alarm. Based on the context, the methods and systems may identify a patient action that may resolve the alarm. A virtual agent may interact with the patient to identify and resolve the alarm without additional caregiver input.

Methods and systems for providing context for alarms and resolving alarms using a virtual agent are described. Inputs including imaging, patient information, and aural, visual, and mechanical patient inputs are analyzed to provide context for an alarm. Based on the context, the methods and systems may identify a patient action that may resolve the alarm. A virtual agent may interact with the patient to identify and resolve the alarm without additional caregiver input.

The present disclosure discloses an attention system and method for users with attention- deficit / hyperactivity disorder (ADHD), the system (100) comprises a server (102) configured to manage tasks and enable communication between a mobile application (104) and remote devices (106) over a wireless communication medium (108) The system includes a patient identification and registration module (115) for user authentication, a patient input module (116) to collect preferences, and a task presentation module (101) for delivering attention tasks in multiple formats. An automated scoring module (105) tracks performance metrics and provides real-time feedback, while an adaptive module (110) adjusts task complexity based on user performance. The system offers personalized rewards through a motivation module (103), stores user data securely with a data storage module (114), and analyses performance over time with a data analysis module (111). The system is configured for both children and adults, ensuring wide accessibility and engagement.

A system is provided.SOLUTION: A system comprising: means for inputting symptom information from a patient before a visit; means for analyzing the input symptom information and searching for an appropriate medical institution or medical worker; means for presenting information on a plurality of medical institutions or medical workers based on the analysis result and allowing the patient to make a selection; means for confirming an appointment with the selected medical institution or medical worker; and means for storing the patient's medical data as electronic data and sharing the data among medical institutions.SELECTED DRAWING: Figure 1

A system and method to collect feedback data from a patient wearing an interface such as a mask when using a respiratory pressure therapy device such as a CPAP device. The system includes a storage device including a facial image of the patient. An interface in communication with the respiratory pressure therapy device collect operational data from when the patient uses the interface. A patient interface collects subjective patient input data from the patient in relation to the patient interface. An analysis module correlates a characteristic of the interface with the facial image data, operational data and subjective patient input data.

The following relates generally to improved clinical symptom analysis. In some embodiments, one or more processors: (1) receive patient input data; (2) obtain patient survey data representing the patient's condition: (3) determine a trend in the patient survey data using a determination algorithm; (4) apply the generative Al algorithm to the patient input data, the patient survey data, and the trend in the patient survey data to produce a report of the trend of the patient's condition; and / or (5) display the report on a display device.

A system and method of collecting feedback data from a patient wearing an interface such as a mask while using a respiratory pressure therapy device such as a CPAP device. The system includes a storage device including a facial image of the patient. An interface in communication with the respiratory pressure therapy device, the interface collecting operational data from the patient while using the interface. The patient interface collects subjective patient input data from the patient regarding the patient interface. An analysis module correlates features of the interface with the facial image data, the operational data, and the subjective patient input data.

The application provides a method and device for training a model, and a method and device for predicting a sub-diagnosis intention. An electronic device supports obtaining a target main diagnosis intention of a patient in a process of queuing for diagnosis, and predicting and outputting, based on a prediction model of a sub-diagnosis intention, a sub-diagnosis intention in which a patient inputs a sub-named entity from a plurality of sub-diagnosis intentions cascaded with the target main diagnosis intention, so that the patient can input a sub-named entity to the output sub-diagnosis intention, to collect answers of the patient to questions in advance automatically by using time of the patient in the process of queuing for diagnosis, and facilitate automatic recording of a disease of the patient, so as to avoid omission and misdiagnosis or missed diagnosis. Furthermore, after the patient enters a diagnosis stage, a doctor can directly obtain answers of the patient to questions, without real-time questioning of the patient by the doctor, so as to save time of the doctor and the patient in the process of diagnosis.

Techniques for assessing a visual field of a patient are presented. The techniques use a system that includes: an immersive headset; a patient input device; and an electronic processor coupled to the immersive headset and to the patient input device, where the electronic processor is configured to perform actions that include: causing the immersive headset to display a first sequence of stimuli to a first eye of the patient, where respective locations of individual stimuli from the first sequence of stimuli are selected from among locations that are equidistantly spaced within quadrants of a field of view of the first eye of the patient; receiving, from the patient input device, responses indicative of whether the patient perceived individual of the first sequence of stimuli; adapting the first sequence of stimuli based at least on the responses; and reporting a patient visual deficit pattern based on the causing and the receiving.

To provide an information processing system that can improve communication between patients and healthcare professionals. [Solution] The information processing system comprises: a pre-information acquisition means for acquiring patient information based on patient input; a prescription pattern determination means for determining one of a plurality of prescription patterns based on the pre-information acquisition means; a questionnaire generation means for generating a questionnaire corresponding to the prescription pattern determined by the prescription pattern determination means; a questionnaire result acquisition means for acquiring the patient's response results to the questionnaire generated by the questionnaire generation means; a supplementary explanation generation means for generating supplementary explanations for the patient based on the response results acquired by the questionnaire result acquisition means; and a feedback generation means for generating feedback for healthcare professionals based on the response results acquired by the questionnaire result acquisition means.

A system including an implant for delivering therapy to a patient, an energizing pod for wirelessly energizing the implant, a local subsystem including one or more mobile or wearable communication / processing devices capable of wirelessly controlling the operation of the implant and of communicating with a clinician workstation to receive a digital prescription data file (DPF) including therapy parameters from the clinician workstation. The local subsystem is configured to receive patient input selecting values of one or more patient modifiable therapy parameters, to generate an implant control data file (ICF) including the values of the patient modifiable therapy parameters and to wirelessly transmit the ICF file to the implant via the energizing pod for controlling the operation of the implant.

The invention discloses an input and output monitoring and early warning system and method based on multi-modal data fusion, and the system comprises an input and output data collection module which is used for collecting input data and output data of a patient; the local processing module is used for storing the collected input data and output data in local equipment of the patient and preprocessing the input data and the output data to obtain categories, water content and confidence of the input and output of the patient; the data processing module is used for carrying out secondary processing on the data of which the confidence is lower than a preset confidence threshold to obtain water content correction results of the input and output of the patient, and generating a patient input and output report; and the early warning module is used for obtaining the patient input and output report and sending out early warning to the patient and medical care. According to the invention, the comprehensiveness, accuracy and patient compliance of data acquisition can be improved, so that accurate input and output prediction and personalized analysis are realized, a more scientific basis is provided for clinical treatment, and the treatment effect is improved.

An intelligent automated patient assessment system comprising a system processor; software stored on a tangible medium operationally coupled to the system processor; and a user interface operationally coupled to the processor whereby, in response to the user interface, the processor executes the software to automatically output patient assessment results in response to patient inputs. In the illustrative embodiment, the processor is programmed with a natural language processor coded for automated sentiment detection. The system detects and processes neutral, positive and negative 10 sentiment for automated mood detection. Mood detection is then incorporated into an assessment provided to a clinician. The system further includes code for activating an alarm in response to detected negative sentiment.

This application designs a method for implementing multi-dimensional Q&A for thyroid diseases, including: S1. After the patient inputs a question, the intention recognition model in the first layer of the multi-dimensional Q&A system determines whether the question is a concern or consultation intention. If the concern intention is hit, enter the concern Q&A; otherwise, enter the consultation intention. S2. Enter the consultation intention, establish a multi-round Q&A model based on the semantic slot template, and conduct the second-layer Q&A. S3. When the intention not summarized in the semantic slot template or the knowledge queried in the knowledge graph is empty, transfer to the FAQ retrieval Q&A, and let the retrieval robot be the fallback reply for the last link of intelligent consultation. S4. Through multiple fixed template Q&A interactions, the multi-dimensional Q&A system conducts logical judgments to achieve the patient's self-disease assessment and self-diagnosis. Through the above design, this application can achieve multi-dimensional Q&A in the field of intelligent consultation for thyroid diseases, thereby improving the intelligent Q&A coverage rate and accuracy.

Disclosed herein are methods, devices, and systems for the enhanced monitoring of visual function via telemedicine to detect early onset of changes and abnormalities associated with disease. The systems include a cloud environment or neural network communicating various tests and images to a client device in which a user / patient is properly positioned to view a display of the client device, receive stimuli, and provide patient input which is evaluated in terms of timing and substance to generate a contrast-sensitivity map of a visual function for the patient. Various ocular tests are described for implementation in a new home-based computer environment rather than using expensive and specific medical equipment in a doctor's office.

A method comprises establishing communication between a therapy device implantable in a patient and a consumer electronic device operable by the patient. The method comprises controlling, by the consumer electronic device, a predetermined set of therapy device functions in response to patient inputs to the consumer electronic device. The method also comprises transmitting therapy data from the therapy device to the consumer electronic device. The method further comprises presenting therapy data on a display of the consumer electronic device.

A decision support system that aids healthcare practitioners in making more informed clinical decisions and avoiding errors related to diagnosis and treatment of diseases. The system utilizes several data points from the patient history and clinical findings input by the patient and the doctor, to help the doctor make a more accurate diagnosis and develop a more informed treatment plan that incorporates not just drugs and procedures, but also dietary and lifestyle interventions. A system of the present disclosure comprises dosage calculator, symptom checker, differential diagnosis, drug interaction checker, side effect checker, nutritional analyzer and drug-food interaction checker input pathways and corresponding database compartments. Output data is generated in correspondence with patient input data and stored on a database server, where it is correlated with patient outcomes over time and improved through machine learning.